Institutional networks and self-organized adaptation: Tracing the democratic architectures of climate response
https://doi.org/10.5878/4s7a-c964
This project, “Institutional Networks and Self-organized Adaptation”, examines the role of rural institutions and public support systems in shaping responses to shocks and stressors in rural India & Nepal during 2020-21. We include stressors related to COVID-19, climate, health, and other challenges identified by rural households.
The data includes:
- Village information on demographics, infrastructure, and natural resources
- Village level institutions involved in livelihood support and adaptive responses
- Networks of interaction between these institutions
- Household information on demographics, livelihoods, interaction with institutions, shocks & stressors, and responses to these stressors
Household level data includes high-frequency repeat visits (approximately monthly) to gather detailed information about stressors and responses over the calendar year.
This dataset contains 480 households nested within 16 local governmental units in the Himalayan region. This includes 8 villages in the Kangra District of India’s northern state of Himachal Pradesh and the Dhulikhel and Ramechhap Districts of east central Nepal.
Through repeated visits during the calendar year, we have captured 8694 self-observed shocks and stressors, i.e. "threats" (3550 in India & 5144 in Nepal), and 5859 responses to cope or adapt to these threats (2553 in India, 3306 in Nepal).
Documentation files
Documentation files
Citation and access
Citation and access
Data access level:
Creator/Principal investigator(s):
- Divya Gupta - Binghamton University
- Suchita Shrestha - University of Melbourne
- Kamal Devkota - KU Leuven
- Roshani Bulkunde - Georgia Institute of Technology
- Devanshi Singh - University of California Berkeley
- Binod Adhikari - Swedish University of Agricultural Sciences Uppsala - Department of Urban and Rural Development
- Parbati Pandey - Southasia institute of advanced studies
- Rajesh Rana - Kangra Integrated Sciences and Adaptation Network (KISAN)
- Vijay Guleria - Kangra Integrated Sciences and Adaptation Network (KISAN)
Research principal:
Principal's reference number:
- SLU.sol.2023.IÄ-21
Data contains personal data:
Yes
Type of personal data:
Data contains personal data about household demographics, livelihoods, socio-economic and environmental stressors, and interaction with political actors and public institutions.
Code key exists:
Yes
Sensitive personal data:
Yes
Data contain other protected information:
Yes
Type of protected information:
Data contains information about household ethnicity & caste, interactions with political actors, and details about personal challenges and losses, data which is sensitive and needs to be protected.
Citation:
Language:
Method and outcome
Method and outcome
Data collection - Self-administered questionnaire: Paper
Data collection - Self-administered questionnaire: Paper
Geographic coverage
Geographic coverage
Administrative information
Administrative information
Topic and keywords
Topic and keywords
Relations
Relations
Metadata
Metadata
Version 1
